Handle various cases of multiplying transpose-wrapped matrices

See test cases. I hit these while taking third-order derivatives of
matrix multiplies (whose gradient definitions use transpose).

src/tracker/lib/array.jl

@@ -361,6 +361,9 @@ x::TrackedVector  * y::TrackedVector  = track(*, x, y)
 @grad a::AbstractMatrix * b::AbstractVecOrMat =
   data(a)*data(b), Δ -> (Δ * transpose(b), transpose(a) * Δ)
 
+@grad a::TrackedMatrix{<:Any, <:Transpose} * b::AbstractVecOrMat =
+  data(a)*data(b), Δ -> (transpose(b * transpose(Δ)), transpose(a) * Δ)
+
 # NNlib
 
 using NNlib
@@ -412,7 +415,7 @@ end
 
 using ForwardDiff: Dual, partials, value
 
-trim(x, Δ) = reshape(Δ, ntuple(i -> size(Δ, i), Val(ndims(x))))
+trim(x, Δ) = ndims(Δ) == ndims(x) ? Δ : reshape(Δ, ntuple(i -> size(Δ, i), Val(ndims(x))))
 
 unbroadcast(x::AbstractArray, Δ) =
   size(x) == size(Δ) ? Δ :

test/tracker.jl

@@ -328,4 +328,14 @@ end
   @test back([1, 1]) == (32,)
 end
 
+@testset "transpose" begin
+  let f = (x,a,b)->(x = transpose(x); x * a + x * b),
+      g = x->(a = transpose(x); b = transpose(a); b * [1.0 1.0; 2.0 3.0] + a * [1.0 1.0; 2.0 3.0])
+      @test gradient(x->sum(f(x, [1.0; 1.0], [1.0; 1.0])), [1.0 1.0; 1.0 1.0])[1] ==
+        [2.0 2.0; 2.0 2.0]
+      @test gradient(x->sum(g(x)), [1.0 1.0; 1.0 1.0])[1] ==
+        [4.0 7.0; 7.0 10.0]
+  end
+end
+
 end #testset